Applied Mathematics & Information Sciences
Image deblurring is a classic problem which has been extensively studied in image processing. The challenge of image deblurring is how to devise efficient and reliable algorithms for recovering the original, sharp image from a blurred and noisy one. In this paper, we consider the implementation of the LSMR method for computing an approximate solution of an ill-posed problem arising from image deblurring. When equipped with a stopping rule based on the discrepancy principle, the LSMR method acts as a regularization method. The numerical examples illustrate that the LSMR method is able to give restored images of higher quality with less computational effort than other widely used regularization methods.
Digital Object Identifier (DOI)
Xu, Hao; Huang, Ting-Zhu; Lv, Xiao-Guang; and Liu, Jun
"The Implementation of LSMR in Image Deblurring,"
Applied Mathematics & Information Sciences: Vol. 08:
6, Article 44.
Available at: https://digitalcommons.aaru.edu.jo/amis/vol08/iss6/44